Molecular Alterations and Severe Abnormalities in Spermatozoa of Young Men Living in the "Valley of Sacco River" (Latium, Italy): A Preliminary Study.

The Valley of Sacco River (VSR) (Latium, Italy) is an area with large-scale industrial chemical production that has led over time to significant contamination of soil and groundwater with various industrial pollutants, such as organic pesticides, dioxins, organic solvents, heavy metals, and particularly, volatile organic compounds (VOCs). In the present study, we investigated the potential impact of VOCs on the spermatozoa of healthy young males living in the VSR, given the prevalent presence of several VOCs in the semen of these individuals. To accomplish this, spermiograms were conducted followed by molecular analyses to assess the content of sperm nuclear basic proteins (SNBPs) in addition to the protamine-histone ratio and DNA binding of these proteins. We found drastic alterations in the spermatozoa of these young males living in the VSR. Alterations were seen in sperm morphology, sperm motility, sperm count, and protamine/histone ratios, and included significant reductions in SNBP-DNA binding capacity. Our results provide preliminary indications of a possible correlation between the observed alterations and the presence of specific VOCs.

A novel human biomonitoring study by semiconductor gas sensors in Exposomics: investigation of health risk in contaminated sites.

Two areas in central-southern Italy Land of Fires in Campania and Valley of Sacco river in Lazio are known to be contaminated sites, the first due to illegal fly-tipping and toxic fires, and the second due to an intensive industrial exploitation done by no-scruple companies and crooked public administration offices with dramatic consequences for environment and resident people. The work is intended to contribute to Human BioMonitoring (HBM) studies conducted in these areas on healthy young male population by a semiconductor gas sensor array trained by SPME-GC/MS. Human semen, blood and urine were investigated. The fingerprinting of the Volatile Organic Compounds (VOCs) by a gas sensors system allowed to discriminate the different contamination of the two areas and was able to predict the chemical concentration of several VOCs identified by GC/MS.

Effects of a Lifestyle Change Intervention on Semen Quality in Healthy Young Men Living in Highly Polluted Areas in Italy: The FASt Randomized Controlled Trial.

BACKGROUND: Human semen quality is affected by lifestyle and environmental factors. OBJECTIVE: To evaluate the short-term effects of a diet and physical activity intervention on semen quality of healthy young men living in highly polluted areas of Italy. DESIGN, SETTING, AND PARTICIPANTS: A randomized controlled trial was conducted. Healthy young men were assigned to an intervention or a control group. INTERVENTION: A 4-mo Mediterranean diet and moderate physical activity program. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcomes were sperm concentration, motility and morphology, concentration of round cells, and semen total antioxidant capacity. Secondary outcomes were adherence to Mediterranean diet and physical activity. All outcomes were measured twice, at the enrollment (t0) and at the end of the intervention (t4). RESULTS AND LIMITATIONS: A total of 263 individuals attended all visits, and underwent examinations and laboratory analyses: 137 in the intervention group and 126 in the control group. The adherence to Mediterranean diet and physical activity level increased more in the intervention group than in the control group from t0 to t4. Sperm concentration, total and progressive motility, and proportion of normal morphology cells increased in the intervention group but decreased in the control group, with statistically significant differences between the two groups at t4. The total antioxidant capacity increased in the intervention group but decreased in the control group, from t0 to t4. CONCLUSIONS: Study results showed that an intervention based on Mediterranean diet and regular physical activity can determine an improvement of semen quality in healthy young men. PATIENT SUMMARY: Our study aimed to evaluate the effect of a lifestyle intervention on semen quality of healthy young men. We assigned the 263 enrolled individuals to an intervention or a control group. The intervention group followed a 4-mo Mediterranean diet and moderate physical activity program, at the end of which the participants showed an improvement of semen quality parameters.

Blood, urine and semen Volatile Organic Compound (VOC) pattern analysis for assessing health environmental impact in highly polluted areas in Italy.

Volatile Organic Compound (VOC) analysis is usually applied in pollution assessment by checking for toxic or harmful volatile compounds in air, water and soil samples. In this study, exogenous VOCs and their derivatives, metabolized by cells, were valued into specific body fluids. In particular, the VOC profiles of blood, urine and human semen samples collected from young men living in two high pollution areas in Italy, i.e. Land of Fires and Valley of Sacco River, were fingerprinted. The analysis is based on Headspace Solid Phase MicroExtraction (HS-SPME) followed by Gas Chromatography-Mass Spectrometric detection (GC-MS). The volatile composition of the three body fluids showed that some VOCs are in common between blood, urine and human semen samples, whereas others are present only in a body fluid. Some compounds, as well as also some chemical classes show a higher affinity for a specific body fluid. Statistical analysis allowed to discriminate the two contaminated areas and identify those compounds which significantly contribute to the two areas classification. Some of these compounds are toxic and found prevalently in Valley of Sacco River samples, correspondingly to sperm analysis results for young men living in this zona worse than those living in Land of Fires.

Artificial intelligence techniques for embryo and oocyte classification.

One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in the capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. This work concentrates the efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the local binary patterns). The proposed system was tested on two data sets of 269 oocytes and 269 corresponding embryos from 104 women and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they show an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection. One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in our capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. In this work, we concentrate our efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the 'local binary patterns'). The proposed system is tested on two data sets, of 269 oocytes and 269 corresponding embryos from 104 women, and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they showed an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection.

Correlation of oocyte morphometry parameters with woman's age.

PURPOSE: Aim of this study was to evaluate morphometric parameters of metaphase II oocytes, including cytoplasm diameter (CD), zona pellucida thickness (ZPT) and width of the perivitelline space (PS), in relation with zona pellucida birefringence, spindle presence and age of the woman. METHODS: Oocytes were classified into groups according to zona birefringence (low or high zona birefringence, LZB and HZB, respectively) and presence or absence of a visible spindle (SP and aSP, respectively). RESULTS: HZB oocytes showed a thicker zona (17.7 ± 0.3 µm) than LZB oocytes (16.7 ± 0.3 µm, p < 0.01). Moreover, PS was narrower in HZB and SP oocytes than in LZB (p < 0,001) and aSP (p < 0,05) oocytes. Finally, we found that CD and ZPT linearly decrease with age of the woman (CD r = 0.028: p < 0.01; ZPT r = 0.050: p < 0.0001). CONCLUSION: Our results evidence an association in human oocytes between zona pellucida and spindle birefringence and defined morphometric parameters and a decrease of oocyte size and ZPT as a function of women's age.